دوره 30، شماره 56 - ( 1401 )
جلد 30 شماره 56 صفحات 30-7 |
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Ghasemi M, Abedi S, Mohtashami A. Presenting a Model for Predicting Tax Evasion of Guilds Based on Data Mining Technique. J Tax Res 2023; 30 (56) :7-30
URL: http://taxjournal.ir/article-1-2215-fa.html
URL: http://taxjournal.ir/article-1-2215-fa.html
قاسمی محمد، عابدی صادق، محتشمی علی. ارائه الگوی پیش بینی فرار مالیاتی اصناف مبتنی بر تکنیک داده کاوی. پژوهشنامه مالیات. 1401; 30 (56) :7-30
محمد قاسمی 
، صادق عابدی* 1، علی محتشمی
، صادق عابدی* 1، علی محتشمی
1- ، Aabedi.sadegh@gmail.com
چکیده: (991 مشاهده)
در این پژوهش با توجه به اهمیت موضوع و خلأ پژوهشهای پیشین، یک مدل پیش بینی فرار مالیاتی اصناف مبتنی بر تکنیک داده کاوی ارائه میگردد. دادههای مورد تحلیل شامل بررسی 5600 پرونده مالیاتی کلیه اصناف دارای کد مالیاتی در استان قزوین طی سال های ۹۳ تا ۹۸ میباشد. پرونده مالیاتی مرتبط با اصناف در پنج گروه مالیاتی شامل گروه صنفی صاحبان دفاتر رسمی، گروه صنفی مشاورین املاک، گروه صنفی تالارهای پذیرایی، رستوان و مشاغل وابسته، گروه صنفی خدمات ارتباطی و گروه صنفی نمایشگاه و فروشگاه لوازم خودرویی و مشاغل وابسته می باشند. جهت مدل سازی از الگوی کلاس بندی درخت تصمیم استفاده گردید. نتایج نشان میدهد، مدل درخت تصمیم بر اساس دادههای موجود، مدل مناسبی جهت پیش بینی محسوب میشود. معیار پوشش برابر 68 %، معیار کاپا برابر 0.612 بدست آمده است که عملکرد خوب مدل ساز را نشان میدهد. همچنین با استفاده از تکنیک Cross Validation صحت اعتبار مدل پیش بینی مورد آزمون قرار گرفت تا با اطمینان بیشتری درصد عملکرد مدل سازی تخمین زده شود. معیار صحت برابر 67.79% نشان از قابلیت اطمینان مناسب جهت مدل پیش بینی میباشد. نتایج حاصل از این پژوهش میتواند در تدوین راهبردهای عملیاتی مبنی بر داده کاوی جهت پیش بینی فرار مالیاتی اصناف در استانها مورد بهره برداری قرار گیرد.
نوع مطالعه: پژوهشي |
موضوع مقاله:
مدیریتی
دریافت: 1401/12/24 | پذیرش: 1401/12/10 | انتشار: 1401/12/10
دریافت: 1401/12/24 | پذیرش: 1401/12/10 | انتشار: 1401/12/10
فهرست منابع
1. Rezaqoli Zadeh M, Aghii M, Alami A.H. (2019). Analysis of Tax Evasion in Iran by Multiple Index-multiple Causes (MIMIC) Method. Majlis and Strategy. 26(97): 191 - 226, (Persian).
2. Khodaparast M, Sultan Hosseini M, Salimi M. (2019). Estimating the Relative Share of Managerial Factors on Tax Evasion of Athletes and Professional Coaches of Sports Clubs in Isfahan Province. Physiology and Management Researches in Sports. 10(2):101-113, (Persian).
3. Dehghani S, Mousavi Jahromi Ye, Abdoli Q. (2019). A New Approach in Explaining the Phenomenon of Tax Evasion. Economic Research. 53(1): 1 - 23, (Persian).
4. Mohammadi Khiare M. (2019). Investigation of the Impact of Tax Evasion and Corruption on Entrepreneurship: the Case Study of OECD Countries. Entrepreneurship Development. 11(3): 501 - 520, (Persian).
5. Omidpour R, Pajhoyan J. (2018). Tax Evasion in the Income Tax Base of Legal Entities in Iran (Annual Estimates 1352-1392). Financial Economy (Financial Economy and Development). 11(39): 27 - 56, (Persian).
6. Rezaei Siabidi M. (2018). Ways to Fight and Prevent Tax Evasion. Yar Law, 4(4): 145- 159, (Persian).
7. Amiri M. (2018). Behavioral Economics and Tax Evasion. Economic Research Journal. 17(64): 95- 130, (Persian).
8. Fetras M H, Delai Milan A. (2017). Investigating the Underground Economy and Tax Evasion in the Framework of Dynamic Stochastic General Equilibrium (DSGE) Models. Economic Growth and Development Studies 7(25): 65 -84, (Persian).
9. Karamkhani J, Weysmoradi A, Ali Madd Z. (2017). Investigating the Effectiveness of Tax Crimes in Preventing Tax Evasion in the Value Added Tax System among Taxpayers in Ilam Province. State Accounting. 2(4):25 -36, (Persian).
10. Karimi Patanlar S, Gilak Hakimabadi M T, Saber N F. (2016). Examining the Effect of Government Effectiveness on Reducing Tax Evasion in Selected Countries. Tax Research Journal. 23(27): 63 - 90, (Persian).
11. Hamidi N, Mohammadzadeh A, Mohammadi F. (2016). Investigating the Position of Tax Crimes in Preventing Evasion in the Value Added Tax System (Case Study of Qazvin Province). Tax Research. 23(27): 147 - 166, (Persian).
12. Maddah M, Khaleq Panah Z. (2016). Tax Evasion in Iran's Imports, the Approach of the Hybrid Model of Artificial Neural Network and Gradual Cooling Algorithm. Planning and Budgeting. 20(2): 85 - 102, (Persian).
13. Zahi N, Mohammad Khanali S. (2011). Investigation of Factors Affecting Tax Evasion (Case Study of East Azarbaijan Province). Tax Research Paper. 18(9): 25 -60, (Persian).
14. Taqvi Fard M.T, Raisi Vanani I, Panahi Re. (2018). Prospective Analysis of Tax Evasion Detection in Modian Value Added Tax using Classification and Clustering Algorithms. Tax Research Journal. 25(35): 11 - 35, (Persian).
15. Laridasht M, Qaim Masaki K, Kahrami Q. (2017). Investigation of Factors Affecting Tax Evasion in South Khorasan Province with Emphasis on Cultural Components. Value and Behavioral Accounting. 1(2): 139 164, (Persian). [DOI:10.18869/acadpub.aapc.1.1.139]
16. Rahimi KIA E, Mohammadi S, Ghazanfari M. (2016). Tax Evasion Detection using a Combined Intelligent System. Tax Research Journal. 23(2): 135 - 163, (Persian).
17. Tasgir M, Gharibi M. (2016). Application of Data Mining Methods to Improve the Performance of Tax Evasion Detection. Tax Research Journal. 23(28): 95 - 116, (Persian).
18. Khosravi T, Pezhuyan J. (2014). The Effect of Corporate Taxes on Private Sector Investment using the Banks Approach, Financial Economics (Financial Economics and Development). 7(25): 95 - 121, (Persian).
19. Amiri R. (2019). Tax Avoidance, Tax Risk and Debt Maturity in Companies Listed on the Tehran Stock Exchange, Islamic Azad University, Marvdasht Branch, Master's Thesis, (Persian).
20. Panahi Re. (2017). Detection of Tax Evasion of VAT Taxpayers using Data Mining Methods (Case Study: VAT Taxpayers of Tehran), Allameh Tabatabai University, Master's Thesis, (Persian).
21. Moghimi Nia A. (2009). Designing a Suitable Solution for Determining and Calculating Business Tax Coefficients, Research Journal on Taxation. Scientific Quarterly Journal of the Tax Administration of Iran. 16 (3): 38-9, (Persian).
22. Arab Mazar A.A, Dehghani A. (2009). Estimating the Efficiency of Taxes on the Income of Businesses and Legal Entities, Research Journal of Taxation. 17(7): 45 - 64, (Persian).
23. Khosro P, Elizabeth Soltani S. (2009). Estimation of Tax Capacity in Fars Province, Tax Research Journal, Scientific Quarterly of the National Tax Affairs Organization, 16(1): 29-49, (Persian).
24. Yamen A. (2018). Impact of Institutional Environment Quality on Tax Evasion: A Comparative Investigation of Old Versus New EU Members. Journal of International Accounting, Auditing and Taxation. 32: 17-29. [DOI:10.1016/j.intaccaudtax.2018.07.001]
25. Abdixhiku L. B, Krasniqi G. (2017).Pugh and I. Hashi, Firm-level Determinants of Tax Evasion in Transition Economies, Economic Systems.41(3):354-366. [DOI:10.1016/j.ecosys.2016.12.004]
26. Stankevicius E. (2015). Hybrid Approach Model for Prevention of Tax Evasion and Fraud. Social and Behavioral Sciences.213: 383-389. [DOI:10.1016/j.sbspro.2015.11.555]
27. Khalil S and Sidani Y. (2020). The Influence of Religiosity onTax Evasion Attitudes in Lebanon. Journal of International Accounting. Auditing and Taxation. 40: 220-235. [DOI:10.1016/j.intaccaudtax.2020.100335]
28. Agarwal S, Li K, Yu Qin, Jing W, Yan J. (2020). Tax Evasion, Capital Gains Taxes, and the Housing Market. Journal of Public Economics. 188: 104-122. [DOI:10.1016/j.jpubeco.2020.104222]
29. Di Gioacchino D, Fichera D. (2020). Tax Evasion and Tax Morale: A Social Network Analysis. European Journal of Political Economy. 65: 121-149. [DOI:10.1016/j.ejpoleco.2020.101922]
30. Demir B, Javorcik B. (2020).Trade Policy Changes, Tax Evasion and Benford's Law. Journal of Development Economics. 144: 152-178. [DOI:10.1016/j.jdeveco.2020.102456]
31. Yousefi K, Vesal M, Pilvar Hanifa. (2020). Import Tax Evasion and Avoidance: Evidence from Iran.The Quarterly Review of Economics and Finance. 75: 31-39. [DOI:10.1016/j.qref.2019.05.010]
32. Ruan J, Yan Z, Dong B, Zheng Q, Qian B. (2019). Identifying Suspicious Groups of Affiliated-transaction-based Tax Evasion in Big Data. Information Sciences. 477: 508-532. [DOI:10.1016/j.ins.2018.11.008]
33. Hung F.S. (2017). Explaining the Nonlinearity of Inflation and Economic Growth: The Role of Tax Evasion .International Review of Economics & Finance. 52: 436-445. [DOI:10.1016/j.iref.2017.03.008]
34. Didimo W, Giamminonni L, Liotta G, Montecchiani F, Pagliuca D. A. (2018). Visual Analytics System to Support Tax Evasion Discovery. Decision Support Systems. 110: 71-83. [DOI:10.1016/j.dss.2018.03.008]
35. González P.C, Velásquez J.D. (2017). Characterization and Detection of Taxpayers with False Invoices using Data Mining Techniques. Expert Syst. Appl. 40 (5): 60-81.
36. Assylbekov Z, Melnykov I, Bekishev R, Baltabayeva A, Bissengaliyeva D, Mamlin E. (2016). Detecting Value-added Tax Evasion by Business Entities of Kazakhstan. Intelligent Decision Technologies Springer. 56: 37-49. [DOI:10.1007/978-3-319-39630-9_4]
37. Chen Y. S, Cheng C. H. (2010). A Delphi-based Rough Sets Fusion Model for Extracting Payment Rules of Vehicle License Tax in the Government Sector. Expert Syst. Appl. 37(3): 2161-2174. [DOI:10.1016/j.eswa.2009.07.027]
38. Devereux M.P, Griffith R, Klemm A. (2002). Can International Tax Competition Explain Corporate Income Tax Reforms. Econ. 35: 323-341.
39. Ferrantino M.J, Liu X, Wang Z. (2012). Evasion Behaviors of Exporters and Importers: Evidence from the US-China Trade Data Discrepancy. J. Int. Econ. 86 (1): 141-157. [DOI:10.1016/j.jinteco.2011.08.006]
40. Goumagias N.D, Hristu-Varsakelis D, Saraidaris A. (2012). A Decision Support Model for Tax Revenue Collection in Greece. Decis. Support Syst. 53 (1): 76-96. [DOI:10.1016/j.dss.2011.12.006]
41. Hsu K. W, Pathak N, Srivastava J, Tschida G, Bjorklund E. (2015). Data Mining Based on Tax Audit Selection: a Case Study of a Pilot Project at the Minnesota Department of Revenue. In: Real World Data Mining Applications, Springer. 89: 221-245. [DOI:10.1007/978-3-319-07812-0_12]
42. Jia S. (2016). Tax Losses in China: Estimates, Analysis and Countermeasures. Friends Account. 13: 39-40.
43. Sikka P. (2010). Corporate Social Responsibility and Tax Avoidance in Accounting Forum. 34: 153-168. [DOI:10.1016/j.accfor.2010.05.002]
44. Tian F, Lan T, Chao K.M, Godwin N, Zheng Q, Shah N, Zhang F.(2016). Mining Suspicious Tax Evasion Groups in Big Data. IEEE Trans, Knowl. Data Eng. 28(10): 2651-2664. [DOI:10.1109/TKDE.2016.2571686]
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